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Crash Course: Artificial Intelligence
Algorithmic Bias and Fairness #18
Season 1
Episode 18
We're going to talk about five common types of algorithmic bias we should pay attention to: data that reflects existing biases, unbalanced classes in training data, data that doesn't capture the right value, data that is amplified by feedback loops, and malicious data.
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10:50
In our final episode of Crash Course AI, we're going to look towards the future.
13:01
Jabril tries to make an AI to settle the question once and for all.
11:08
Search engines are just AI systems that try to help us find what we’re looking for.
14:33
We need to save Jabril and John Green Bot’s movie nights.
10:19
We’re going to talk about recommender systems.
9:56
We’re going to focus on the benefits of humans and AI working together.
13:06
We create a game and then build an AI to destroy it.
11:11
One of the best test spaces for building new AI systems are games.
9:52
Robots are built to perform specific tasks.
13:01
Symbolic AI represents problems using symbols and then uses logic to search for solutions.
11:07
Reinforcement Learning.
15:17
Let’s try to help John Green Bot sound a bit more like the real John Green using NLP.